Communication protocols and sensing coverage in mobile ad hoc and wireless sensor networks.

摘要

In recent years, Mobile Ad-hoc Networks (MANETs) and Wireless Sensor Networks (WSNs) have received tremendous attention due to their desired features of self-configuration and self-maintenance. To address and mitigate the problems such as Broadcast Storm, latency, and congestion, this thesis presents a routing protocol for MANETs and a data transport protocol for WSNs. In addition, the coverage problem in WSNs is discussed with innovative solutions.;To address broadcast storm problems, stale route, faulty nodes and latency in MANETs, this thesis proposes a Fault resilient MANET Routing protocol, FaRM, in which a density-first route selection technique is used to select the most robust routes during route discovery. A local self-recovery mechanism is proposed for route maintenance. The performance evaluation based on ns-2 shows significant improvements in FaRM's throughput, overhead, scalability and stability in demanding environments with high mobility and heavy traffic loads.;WSNs are generally used for harsh environments involving military actions. Due to severe resource constraints in sensor nodes, including memory space, energy storage, and communication bandwidth, in-network data aggregation is needed. We propose a sensor-to-sink transport protocol, which is suitable for data aggregation and provides reliable upstream packet delivery by dynamically configuring inactive nodes as "monitors" to assist in quick loss detection and recovery. ns-2 based simulations confirm that the monitor-based transport protocol improves the throughput and data delivery rate with the intermittent traffic load and unpredictable node failures.;The goal of deploying a large-scale WSN is to utilize those spatially-distributed autonomous sensors for monitoring certain physical and environmental conditions in a target area. This thesis proposes a topology control technique to configure a densely deployed network and a distributed algorithm to utilize sensors with variable sensing radii for optimal sensing coverage. In addition, a group-based technique is discussed to provide a general approach that can extend any 1-coverage algorithm into k-coverage. The performance comparisons confirmed that the proposed techniques reduce sensing energy consumption and maintain a sound coverage ratio for reliable surveillance.